AI-Driven Risk Assessment in National Security Projects: Investigating machine learning models to predict and mitigate risks in defense and critical infrastructure projects

Artificial Intelligence (AI) is revolutionizing national security and risk assessment, providing enhanced predictive capabilities, automated threat detection, and strategic decision-making tools. This paper explores the integration of AI and machine learning (ML) in national defense strategies, cybersecurity frameworks, and critical infrastructure protection. AI-driven risk assessment models utilize big data analytics, deep learning, and predictive algorithms to proactively identify, classify, and mitigate security threats before they materialize. The study examines AI applications in cyber risk management, military defense systems, fraud prevention, and digital forensics, highlighting their effectiveness in safeguarding government agencies, financial institutions, and energy grids. Additionally, the paper discusses ethical considerations, algorithmic biases, and regulatory challenges associated with AI-driven risk assessment. The findings emphasize the increasing reliance on AI in cybersecurity and national security operations, demonstrating how AI-based risk assessment tools contribute to threat intelligence, operational resilience, and automated decision-making in critical security environments. The research concludes with future directions for AI adoption, emerging innovations, and policy recommendations to ensure ethical and effective deployment of AI in national security frameworks.